Do you want to train your own algorithms? Import your predictions, correct them in the annotation tool, and feed them back.

On our secure Cloud or On-premises

On the Cloud, there is nothing to install, no servers to worry about: start right now. On-premises, run tagtog as a docker image in your own infrastructure, Internet access is not required. In both cases, just use your favorite browser. More information.

English, Spanish, Hindi, Bengali, French, Chinese, Japanese, Arabic, Swedish, Dutch, etc. Any language. Unicode support. Left to Right and Right to Left.

Quick training

Use already-trained machines, no new training required. Additionally, upload already-annotated documents or term dictionaries to reduce dramatically the time required for subsequent trainings.

Folders

Organize your text and documents in different folders and levels for a better organization. For example, separate test and production data.

API

Integrate tagtog within your existing pipeline. Use the API to upload text and retrieve the results. You can also use it to search across your text collection or improve your search engine. More information.

Concept Search

Search in text collections not by keyword, but by concept (e.g. find all vehicle technical reports that are related to engine failures). More information.

Entity Normalization

Manage disambiguation. tagtog determines the identity of the annotations assigning unique ids from standard databases such as UniProt or Wikipedia.

You can also upload your own dictionaries to map the annotations to your unique internal references (e.g. product ref). More information.

Big Text

Work with external text sources (e.g. PubMed) or your own files. Process millions of documents with ease.

WHY THEY LOVE IT

We were looking for a way, not only of annotating aspects of the historical documents we work with in order to later extract information from these, but also to do so in an expedite manner and with people that is no expert in NLP or ML. We found tagtog online and it was love at first sight. It was the platform we were looking for.

tagtog has been instrumental in our labeling efforts. We have a complex dataset and several sets of class labels. tagtog allowed our non-technical users to annotate large documents with ease, and allowed our data team to process their work using a sophisticated API. We are extremely satisfied with our investment.

Rachel Lomasky
Chief Data Officer, Wevo Inc.

NEW PDF ANNOTATION TOOL

Annotate over the PDF

Annotate directly over the native PDF layout, annotators love it! 💖

Train your models easily

Import/Export annotations using text offsets or coordinates, tagtog gives you also the text contained in the PDF to facilitate the processing and generation of annotations.